Heraldo Rozas

Unsupervised Domain Adaptation for Anomaly Detection Using Autoencoders and Disentangled Latent Representations

This work demonstrates that domain adaptation can be effectively integrated into unsupervised anomaly detection frameworks, providing a principled pathway to enhance reliability and generalization under variable operating conditions and across multiple similar machines.